External Organisations

  • Galway - Mayo Institute of Technology, Ireland
  • Marine Institute, Ireland
  • CSIC, Spain
  • University of Bergen, Norway
  • L'Institut Français de Recherche pour l'Exploitation de la Mer, France

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Description

The estimation of the biological reference points used in fish stock assessment requires reliable length-at-age information which is usually obtained by counting and measuring seasonal growth marks in otoliths for a representative sample of the population. 

However, for some stocks, clearly defined growth marks do not occur, hampering age estimation and age based assessment and presenting a challenge to the implementation of MSY based management as required under the CFP. For the stocks of anglerfishes (Lophius spp.) and hake (Merluccius merluccius) that are the focus of this tender the reliability of available age-estimation methods is low and the estimation of MSY reference points is problematic. For these stocks, improved growth models are needed to inform length based assessments.

The specified objective of this tender is to analyse microchemistry patterns in otoliths and illicia with the intention of developing improved growth models to inform length-based assessments for the hake and anglerfish stocks of interest.

This proposal addresses that objective by combining the reanalysis of previously collected microchemistry data with additional analyses of existing and newly collected material and a comprehensive analysis of length distributions from available survey data. For hake, direct validation of seasonal microchemistry patterns is possible using existing collections of chemically tagged otoliths. For anglerfish, seasonality will be confirmed using marginal microchemistry analysis of quarterly collections. Pairwise comparisons of otoliths and illicia will allow us to establish the extent to which growth marks and opacity profiles in each structure correspond to seasonal trends in microchemistry.

The tender is funded by EASME/EMFF/2017/012 and is coordinated by Galway Mayo Institute of Technology, Ireland.
StatusActive
Effective start/end date01/01/201813/12/2019
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ID: 158804791